Sentence Compression with Natural Language Generation

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Knowledge Engineering and Management

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 123))

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Abstract

We present a novel unsupervised method for sentence compression which relies on a Stanford Typed Dependencies to extract information items, then generates compressed sentences via Natural Language Generation(NLG) engine. An automatic evaluation shows that our method obtains better results. We demonstrate that the choice of the parser affects the performance of the system.

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References

  1. Clarke, J., Lapata, M.: Models for sentence compression: A comparison across domains, training requirements and evaluation measures. In: Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics, pp. 377–384. Association for Computational Linguistics (2006)

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  2. Genest, P.E., Lapalme, G.: Text generation for abstractive summarization. In: Proceedings of the Second Text Analysis Conference, National Institute of Standards and Technology, Gaithersburg (2010)

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  3. **g, H.: Cut-and-Paste Text Summarization. Ph.D. thesis, Computer Science Department, Columbia University, New York, N.Y (2001)

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  4. Riezler, S., King, T.H., Crouch, R., Zaenen, A.: Statistical sentence condensation using ambiguity packing and stochastic disambiguation methods for lexical-functional grammar. In: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, vol. 1, pp. 118–125. Association for Computational Linguistics (2003)

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© 2011 Springer-Verlag Berlin Heidelberg

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Li, P., Wang, Y. (2011). Sentence Compression with Natural Language Generation. In: Wang, Y., Li, T. (eds) Knowledge Engineering and Management. Advances in Intelligent and Soft Computing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25661-5_46

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  • DOI: https://doi.org/10.1007/978-3-642-25661-5_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25660-8

  • Online ISBN: 978-3-642-25661-5

  • eBook Packages: EngineeringEngineering (R0)

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